library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.2 ✔ tibble 3.3.0
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.1.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(readr)
library(janitor)
##
## Attaching package: 'janitor'
##
## The following objects are masked from 'package:stats':
##
## chisq.test, fisher.test
library(dplyr)
library(lubridate)
library(ggplot2)
rat=read_csv("./data/rat_sighting_raw1.csv", na=c("NA","","0"))|>
janitor::clean_names()
## Warning: One or more parsing issues, call `problems()` on your data frame for details,
## e.g.:
## dat <- vroom(...)
## problems(dat)
## Rows: 259233 Columns: 18
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (9): Created Date, Closed Date, Incident Address, City, Landmark, Facili...
## dbl (2): Unique Key, Incident Zip
## lgl (7): Vehicle Type, Taxi Company Borough, Taxi Pick Up Location, Bridge H...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
glimpse(rat)
## Rows: 259,233
## Columns: 18
## $ unique_key <dbl> 63575470, 63572156, 63580575, 63583963, 63573…
## $ created_date <chr> "2024 Dec 31 10:58:24 PM", "2024 Dec 31 10:49…
## $ closed_date <chr> "2025 Jan 03 09:32:40 AM", "2025 Jan 03 09:32…
## $ incident_zip <dbl> 10475, 10475, 10029, 11215, 10021, 11101, 114…
## $ incident_address <chr> "3550 BIVONA STREET", "3550 BIVONA STREET", "…
## $ city <chr> "BRONX", "BRONX", "NEW YORK", "BROOKLYN", "NE…
## $ landmark <chr> "BIVONA STREET", "BIVONA STREET", "PLEASANT A…
## $ facility_type <chr> "N/A", "N/A", "N/A", "N/A", "N/A", "N/A", "N/…
## $ community_board <chr> "12 BRONX", "12 BRONX", "11 MANHATTAN", "06 B…
## $ borough <chr> "BRONX", "BRONX", "MANHATTAN", "BROOKLYN", "M…
## $ park_borough <chr> "BRONX", "BRONX", "MANHATTAN", "BROOKLYN", "M…
## $ vehicle_type <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ taxi_company_borough <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ taxi_pick_up_location <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ bridge_highway_name <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ bridge_highway_direction <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ road_ramp <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
## $ bridge_highway_segment <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
rat
## # A tibble: 259,233 × 18
## unique_key created_date closed_date incident_zip incident_address city
## <dbl> <chr> <chr> <dbl> <chr> <chr>
## 1 63575470 2024 Dec 31 10:58… 2025 Jan 0… 10475 3550 BIVONA STR… BRONX
## 2 63572156 2024 Dec 31 10:49… 2025 Jan 0… 10475 3550 BIVONA STR… BRONX
## 3 63580575 2024 Dec 31 10:28… 2025 Jan 0… 10029 293 PLEASANT AV… NEW …
## 4 63583963 2024 Dec 31 06:15… 2025 Jan 0… 11215 441 13 STREET BROO…
## 5 63573818 2024 Dec 31 06:10… 2024 Dec 3… 10021 144 EAST 74 S… NEW …
## 6 63572161 2024 Dec 31 06:04… 2024 Dec 3… 11101 21-06 45 AVENUE LONG…
## 7 63578888 2024 Dec 31 05:26… 2025 Jan 0… 11432 160-19 GRAND CE… JAMA…
## 8 63577241 2024 Dec 31 05:05… 2024 Dec 3… 11233 68 SOMERS STREET BROO…
## 9 63583968 2024 Dec 31 04:47… 2025 Jan 0… 11377 47-34 45 STREET WOOD…
## 10 63572155 2024 Dec 31 04:31… 2024 Dec 3… 10456 320 EAST 167 S… BRONX
## # ℹ 259,223 more rows
## # ℹ 12 more variables: landmark <chr>, facility_type <chr>,
## # community_board <chr>, borough <chr>, park_borough <chr>,
## # vehicle_type <lgl>, taxi_company_borough <lgl>,
## # taxi_pick_up_location <lgl>, bridge_highway_name <lgl>,
## # bridge_highway_direction <lgl>, road_ramp <lgl>,
## # bridge_highway_segment <lgl>
rat1= rat |>
mutate(
created_date=parse_date_time(created_date, orders = "Y b d I:M:S p")
)
rat1
## # A tibble: 259,233 × 18
## unique_key created_date closed_date incident_zip incident_address
## <dbl> <dttm> <chr> <dbl> <chr>
## 1 63575470 2024-12-31 22:58:24 2025 Jan 03 09:… 10475 3550 BIVONA STR…
## 2 63572156 2024-12-31 22:49:24 2025 Jan 03 09:… 10475 3550 BIVONA STR…
## 3 63580575 2024-12-31 22:28:26 2025 Jan 02 07:… 10029 293 PLEASANT AV…
## 4 63583963 2024-12-31 18:15:58 2025 Jan 02 10:… 11215 441 13 STREET
## 5 63573818 2024-12-31 18:10:15 2024 Dec 31 06:… 10021 144 EAST 74 S…
## 6 63572161 2024-12-31 18:04:50 2024 Dec 31 06:… 11101 21-06 45 AVENUE
## 7 63578888 2024-12-31 17:26:40 2025 Jan 03 03:… 11432 160-19 GRAND CE…
## 8 63577241 2024-12-31 17:05:26 2024 Dec 31 05:… 11233 68 SOMERS STREET
## 9 63583968 2024-12-31 16:47:45 2025 Jan 03 03:… 11377 47-34 45 STREET
## 10 63572155 2024-12-31 16:31:51 2024 Dec 31 04:… 10456 320 EAST 167 S…
## # ℹ 259,223 more rows
## # ℹ 13 more variables: city <chr>, landmark <chr>, facility_type <chr>,
## # community_board <chr>, borough <chr>, park_borough <chr>,
## # vehicle_type <lgl>, taxi_company_borough <lgl>,
## # taxi_pick_up_location <lgl>, bridge_highway_name <lgl>,
## # bridge_highway_direction <lgl>, road_ramp <lgl>,
## # bridge_highway_segment <lgl>
rat_cleaned = rat1 |>
filter(
year(created_date) >=2019 & year(created_date) <=2024
) |>
mutate(
year=year(created_date),
month = month(created_date, label = TRUE, abbr = FALSE)
)|>
group_by(year,month) |>
summarise(rat_sighting_count = n())
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
rat_cleaned
## # A tibble: 72 × 3
## # Groups: year [6]
## year month rat_sighting_count
## <dbl> <ord> <int>
## 1 2019 January 1020
## 2 2019 February 956
## 3 2019 March 1126
## 4 2019 April 1510
## 5 2019 May 1863
## 6 2019 June 1822
## 7 2019 July 1824
## 8 2019 August 1862
## 9 2019 September 1640
## 10 2019 October 1405
## # ℹ 62 more rows
rat_cleaned$month <- factor(
rat_cleaned$month,
levels = month.name,
ordered = TRUE
)
ggplot(rat_cleaned,
aes(x = month, y = rat_sighting_count)) +
geom_line(aes(group = year, colour = factor(year)), size = 1) +
geom_point(aes(colour = factor(year)), size = 2) +
facet_wrap(~ year, ncol = 2) +
scale_color_brewer(palette = "Dark2") +
labs(
title = "Monthly Rat Sightings in NYC (2019–2024)",
x="Month",
y="Number of Rat Sightings",
color="Year"
) +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
plot_ly(
rat_cleaned,
x = ~month,
y = ~rat_sighting_count,
color = ~factor(year),
type = 'scatter',
mode = 'lines+markers'
) %>%
layout(
title = "Monthly Rat Sightings in NYC (2019–2024)",
xaxis = list(title = "Month"),
yaxis = list(title = "Number of Rat Sightings")
)